




from __future__ import annotations

from collections.abc import Iterator







class     A:



 '''simple docstring'''


 def __init__(							self   :    Tuple		,				A_   :    int    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       value
       lowerCamelCase_							=       None
       lowerCamelCase_							=       None







class     A:



 '''simple docstring'''


 def __init__(							self   :    List[str]		,				A_   :    Node    )  ->      None:

       """simple docstring"""






       lowerCamelCase_							=       tree

 def 							a__					(							self   :    Optional[int]		,				A_   :    Node | None    )  ->      int:

       """simple docstring"""






       if node is None:
             return 0
       return node.value + (
           self.depth_first_search(node.left    ) + self.depth_first_search(node.right    )
       )





 def __iter__(							self   :    Tuple    )  ->      Iterator[int]:

       """simple docstring"""






       yield self.depth_first_search(self.tree    )


if __name__ == "__main__":
 import doctest

 doctest.testmod()











"""simple docstring"""
from datetime import datetime

import matplotlib.pyplot as plt
import torch


def 							A						(				__snake_case: Optional[int]  )    ->		Tuple:

       """simple docstring"""





       for param in module.parameters():
              __magic_name__      				=    False


def 							A						(				)    ->		Optional[Any]:

       """simple docstring"""





       __magic_name__      				=    'cuda' if torch.cuda.is_available() else 'cpu'
       if torch.backends.mps.is_available() and torch.backends.mps.is_built():
              __magic_name__      				=    'mps'
       if device == "mps":
              print(
                  'WARNING: MPS currently doesn\'t seem to work, and messes up backpropagation without any visible torch'
                  ' errors. I recommend using CUDA on a colab notebook or CPU instead if you\'re facing inexplicable issues'
                  ' with generations.'  )
       return device


def 							A						(				__snake_case: int  )    ->		List[Any]:

       """simple docstring"""





       __magic_name__      				=    plt.imshow(__snake_case  )
       fig.axes.get_xaxis().set_visible(__snake_case  )
       fig.axes.get_yaxis().set_visible(__snake_case  )
       plt.show()






def 							A						(				)    ->		List[Any]:

       """simple docstring"""





       __magic_name__      				=    datetime.now()
       __magic_name__      				=    current_time.strftime('%H:%M:%S'  )
       return timestamp